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Events for June 07, 2013
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Meet USC: Admission Presentation, Campus Tour, & Engineering TalkFri, Jun 07, 2013
Viterbi School of Engineering Undergraduate Admission
Receptions & Special Events
This half day program is designed for prospective freshmen and family members. Meet USC includes an information session on the University and the Admission process; a student led walking tour of campus and a meeting with us in the Viterbi School. Meet USC is designed to answer all of your questions about USC, the application process and financial aid. Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m. Please visit https://esdweb.esd.usc.edu/unresrsvp/MeetUSC.aspx to check availability and make an appointment. Be sure to list an Engineering major as your "intended major" on the webform!
Location: Ronald Tutor Campus Center (TCC) - USC Admission Office
Audiences: Everyone Is Invited
Contact: Viterbi Admission Office
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Dr. Andrea Gasparri, Multi-Robot Systems: A Control Perspective II
Fri, Jun 07, 2013 @ 11:00 AM - 12:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
University Calendar
Research Talk by Dr. Andrea Gasparri, Assistant Professor, Engineering Department, Roma Tre University, Italy
Title: Multi-Robot Systems: A Control Perspective II
Abstract: Multi-Robot Systems represent an important research field with a wide variety of topics to be addressed. In recent years a great effort has been made by the research community towards the development of decentralized techniques to provide an adequate level of robustness and flexibility to these systems. This tutorial will provide first a general overview of this research area, focusing on the most important design aspects of a multi-robot system, e.g. control and communication architecture, and illustrating the most important research problems. Then, it will focus on the control aspects of the distributed cooperation problem. In that context, the consensus problem will be first reviewed as a starting point towards the investigation of more refined techniques to achieve spatial aggregation between the robotic units. Furthermore, the connectivity maintenance problem will be introduced, a taxonomy of the approaches available at the state of the art will be derived and some relevant techniques will be described more in detail. Finally, relevant applications in the context of multi-robot systems which rely on the distributed coordination techniques previously introduced will be highlighted.
Biography: Andrea Gasparri received the Graduate degree (cum laude) in computer science in 2004 and the Ph.D. degree in computer science and automation in 2008, both from the University of Rome Roma Tre, Rome, Italy. He is currently an Assistant Professor for the Engineering Department, University of Rome Roma Tre. His current research interests include mobile robotics, sensor networks, and, more generally, networked multi-agent systems.
Dr. Gasparri is a young expert with rapidly growing recognition in the emerging area of distributed networked robotics, a field at the intersection of control, robotics, and networking that is currently gaining in importance. Dr. Gasparri will be visiting USC from May 21 to June 30, 2013.
Organizer(s): Bhaskar Krishnamachari and Gaurav Sukhatme
Sponsored by the Ming Hsieh Institute
For more information: http://mhi.usc.edu/2013/05/01/dr-andrea-gasparri/More Information: Flyer for talks.pdf
Location: EEB 248
Audiences: Everyone Is Invited
Contact: Danielle Hamra
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AI SEMINAR
Fri, Jun 07, 2013 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Benjamin Snyder, Assistant Professor UW-Madison
Talk Title: Dead Languages, and Elbow Grease: Minimally Supervised NLP Models.
Series: AISeminar
Abstract: I will discuss new techniques for inducing accurate statistical models for low resource languages. In the extreme case of language decipherment, we are presented with a text with no knowledge of the language or writing system, and our goal is to identify the phonetic properties of the characters. I will present a Bayesian model that predicts whether letters are consonants or vowels with over 99% accuracy across 503 languages. The model assumes that languages are grouped into latent clusters with shared phonotactic regularities. We perform posterior inference over the identity and shared parameters of these clusters.
In a more common scenario, we are trying to build a model (e.g. for a low resource language) while minimizing our annotation effort. I will present a method based on matrix projections that allows us to quickly identify an optimal set of examples to label. This method outperforms active learning while obviating the need for incremental retraining and bootstrapping. We report error reductions of 25-40% on the tasks of pronunciation modeling and part-of-speech tagging.
Biography: Benjamin Snyder is an assistant professor of computer science at UW-Madison. He completed his PhD at MIT in 2010, receiving the ACM Dissertation Award honorable mention and the George M. Sprowls Award for best PhD thesis in computer science at MIT. He will be visiting ISI For all of June.
Host: David Chiang
Webcast: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=ec818feeeb5b458e87121185990150ef1dLocation: Information Science Institute (ISI) - 11th fl Large CR
WebCast Link: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=ec818feeeb5b458e87121185990150ef1d
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
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NL Seminar- Malte Nuhn "Is Decipherment Difficult"
Fri, Jun 07, 2013 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Malte Nuhn, Aachen University, Germany
Talk Title: "Is Decipherment Difficult"
Series: Natural Language Seminar
Abstract: Abstract: Is it possible to learn useful translations from large amounts of monolingual data to improve machine translation? The intuitive feeling is that learning a language without bilingual data is at least "more difficult than learning from example translations". In this talk, I will present recent results on decipherment: I will show that the decipherment problem is indeed difficult (NP-hard) and what approximations to the original problem can be made without hurting decipherment accuracy much.
Biography: Bio: Having studied Physics and Computer Science at RWTH Aachen University, I'm currently a PhD student at Prof. Ney's Human Language Technology and Pattern Recognition Group in Aachen. I'm particularly interested in applying decipherment techniques to improve machine translation.
Homepage:
http://www-i6.informatik.rwth-aachen.de/~nuhn/
Host: Kevin Knight and Qing Dou
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - Marina Del Rey-11th Flr Conf Rm # 1135
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
